Browsing by Author "Yilmaz, Turgay"
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Conference Object Citation Count: 3Flexible Content Extraction and Querying for Videos(Springer-verlag Berlin, 2011) Koyuncu, Murat; Koyuncu, Murat; Yazici, Adnan; Yilmaz, Turgay; Sert, Mustafa; Information Systems EngineeringIn this study, a multimedia database system which includes a semantic content extractor, a high-dimensional index structure and an intelligent fuzzy object-oriented database component is proposed. The proposed system is realized by following a component-oriented approach. It supports different flexible query capabilities for the requirements of video users, which is the main focus of this paper. The query performance of the system (including automatic semantic content extraction) is tested and analyzed in terms of speed and accuracy.Conference Object Citation Count: 1A Framework for Fuzzy Video Content Extraction, Storage and Retrieval(Ieee, 2010) Koyuncu, Murat; Yilmaz, Turgay; Yildirim, Yakup; Yazici, Adnan; Information Systems EngineeringThis study presents a new comprehensive framework for semantic content extraction from raw video, storage of the extracted data and retrieval of the stored data. Objects, spatial relations between objects, events and temporal relations between events, which are considered as semantic contents of the video, are extracted automatically to a certain extend with the developed approach. Extraction process is supported by manual annotation when automatic extraction is not satisfactory. The extracted information is stored in an intelligent fuzzy object-oriented database in which the database is enhanced with a fuzzy knowledge-based system. Domain specific deduction rules can be defined to derive new information about semantic contents of the video. The database is also supported by an access structure to increase retrieval efficiency. The proposed framework is capable of handling uncertain data arising from annotation process or video nature.Article Citation Count: 20A Fusion-Based Framework for Wireless Multimedia Sensor Networks in Surveillance Applications(Ieee-inst Electrical Electronics Engineers inc, 2019) Koyuncu, Murat; Koyuncu, Murat; Sert, Seyyit Alper; Yilmaz, Turgay; Information Systems EngineeringMultimedia sensors enable monitoring applications to obtain more accurate and detailed information. However, the development of efficient and lightweight solutions for managing data traffic over wireless multimedia sensor networks (WMSNs) has become vital because of the excessive volume of data produced by multimedia sensors. As part of this motivation, this paper proposes a fusion-based WMSN framework that reduces the amount of data to be transmitted over the network by intra-node processing. This framework explores three main issues: 1) the design of a wireless multimedia sensor (WMS) node to detect objects using machine learning techniques; 2) a method for increasing the accuracy while reducing the amount of information transmitted by the WMS nodes to the base station, and; 3) a new cluster-based routing algorithm for the WMSNs that consumes less power than the currently used algorithms. In this context, a WMS node is designed and implemented using commercially available components. In order to reduce the amount of information to be transmitted to the base station and thereby extend the lifetime of a WMSN, a method for detecting and classifying objects on three different layers has been developed. A new energy-efficient cluster-based routing algorithm is developed to transfer the collected information/data to the sink. The proposed framework and the cluster-based routing algorithm are applied to our WMS nodes and tested experimentally. The results of the experiments clearly demonstrate the feasibility of the proposed WMSN architecture in the real-world surveillance applications.Article Citation Count: 11An intelligent multimedia information system for multimodal content extraction and querying(Springer, 2018) Koyuncu, Murat; Koyuncu, Murat; Yilmaz, Turgay; Sattari, Saeid; Sert, Mustafa; Gulen, Elvan; Information Systems EngineeringThis paper introduces an intelligent multimedia information system, which exploits machine learning and database technologies. The system extracts semantic contents of videos automatically by using the visual, auditory and textual modalities, then, stores the extracted contents in an appropriate format to retrieve them efficiently in subsequent requests for information. The semantic contents are extracted from these three modalities of data separately. Afterwards, the outputs from these modalities are fused to increase the accuracy of the object extraction process. The semantic contents that are extracted using the information fusion are stored in an intelligent and fuzzy object-oriented database system. In order to answer user queries efficiently, a multidimensional indexing mechanism that combines the extracted high-level semantic information with the low-level video features is developed. The proposed multimedia information system is implemented as a prototype and its performance is evaluated using news video datasets for answering content and concept-based queries considering all these modalities and their fused data. The performance results show that the developed multimedia information system is robust and scalable for large scale multimedia applications.